Abstract
Shifting HLA typing from serological to molecular methods has enhanced resolution at the possible expense of definitely knowing whether an HLA allele is expressed. Alleles may exhibit variable expression, including “null,” “low,” or “aberrant.” “Null alleles,” designated with the suffix “N,” signify nonfunctional mutated alleles that are not expressed on the cell surface, for example, HLA-A*24:11N.1 Misidentifying null alleles as functional alleles may lead to transplant denials, particularly if relying solely on virtual crossmatching (VCXM) for organ allocation.2 We report a case where the identification of a null allele leads to successful renal transplantation.
A 56-y-old man presented seeking evaluation for second renal transplantation with his sister as a donor. His native kidney disease was diabetic nephropathy. He had undergone transplantation with his wife as a donor 5 y ago. During the third posttransplant year, he developed late-onset antibody-mediated rejection, which culminated in graft loss despite treatment. During the pretransplant immunological evaluation, despite positive anti-HLA antibody screening for classes I and II, intermediate resolution HLA typing by reverse sequence–specific oligonucleotide probe (R-SSOP) showing 5 of 8 mismatches (Figure 1) and single-antigen bead showing potential donor-specific antibodies (DSAs) at A24, B35, and DQ6, flow crossmatch (FCXM) was negative for T and B cells. It was noted that both donors apparently shared a common HLA-A*24, against which DSAs were reported (mean fluorescence intensity ~9000). It was intriguing that FCXM was negative despite high-titer DSAs, especially in the setting of retransplant with a history of severe antibody-mediated rejection and both donors sharing a common HLA-A mismatched loci. A surrogate FCXM done with the previous donor was found to be strongly positive for T and B cells concurrent with the DSA profile. Subsequent retyping of the patient and the new prospective donor on a next-generation sequencing platform revealed that A*24:02 reported in the new donor by R-SSOP was in fact a null allele A*24:11N. This explained the FCXM negativity as null alleles are not expressed on the cell surface. The patient underwent transplantation postdesensitization due to the presence of other DSAs. At 3 mo posttransplant, he maintains a stable creatinine of 1.3 mg/dL, and a surveillance biopsy shows no microvascular inflammation.
FIGURE 1.
Single antigen analysis showing the presence of anti-HLA antibodies against HLA-A*24:02 and B*35 and HLA typing of the recipient, prior donor, and current donor is shown with a typing technique within parenthesis.
This case underscores many practical considerations in histocompatibility testing. First, it demonstrates differential expressivity of alleles, contributing to differential alloreactivity. Although null alleles are a well-known phenomenon in stem cell transplantation,3 their clinical impact on renal transplantation is less known. Second, it emphasizes that combining cell-based crossmatching with solid phase assays has the potential to provide information missed by VCXM alone.4 Third, it stresses the importance of identifying shared unacceptable alleles with previous donors and the possibility of immunological memory in retransplant candidates. Finally, it stresses the necessity of choosing appropriate HLA typing techniques and retyping donors at higher resolution when discrepancies arise. In this instance, the utilization of next-generation sequencing for unexplained alloreactivity elucidated the null allele, which went undetected by R-SSOP typing. Given the growth in transplantation globally and the evolving landscape of histocompatibility testing, there is a need to highlight such intricacies and foster closer collaboration between clinicians and histocompatibility services. Furthermore, comprehensive data on frequencies and association of HLA alleles with variable expression across ethnically diverse populations are essential for the future of histocompatibility testing.5
Footnotes
The authors declare no funding or conflicts of interest.
F.A. and S.S. had full access to all the data and takes full responsibility for the integrity of the data and the accuracy of data analysis and contributed in concept, design, and drafting the article. All authors contributed in acquisition, analysis, and interpretation of data and critical revision of the article.
The authors certify that they have obtained all appropriate consent.
The authors confirm that there was no use of AI-assisted technology for assisting in the writing or editing of the article and no images were manipulated using AI.
Contributor Information
Shabna Sulaiman, Email: shabnasulaimanss@gmail.com.
Benil Hafeeq, Email: benilhafeeq@gmail.com.
Muhammad Suhail Ediyangara Palliparamb, Email: muhammadsuhail008@gmail.com.
Arvind Krishnakumar, Email: arvind.krishnakumar87@gmail.com.
Mohammed S. Khan, Email: drmsk6437@gmail.com.
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